Polish docs and comments in transformers.js

CONTRIBUTING.md

@@ -267,16 +267,16 @@ Follow the steps below to start contributing:
    the pull request.
 
 ### Pull request checklist
-☐ The pull request title should summarize your contribution.  
+☐ The pull request title should summarize your contribution.
 ☐ If your pull request addresses an issue, please mention the issue number in the pull
 request description to make sure they are linked (and people viewing the issue know you
-are working on it).  
+are working on it).
 ☐ To indicate a work in progress please prefix the title with `[WIP]`. These are
-useful to avoid duplicated work, and to differentiate it from PRs ready to be merged.  
-☐ Make sure existing tests pass (`pnpm test`).  
-☐ Make sure the build completes successfully (`pnpm build`).  
-☐ Make sure your code is [formatted properly with Prettier](#code-formatting) (`pnpm format:check`).  
-☐ If adding a new feature, also add tests for it.  
+useful to avoid duplicated work, and to differentiate it from PRs ready to be merged.
+☐ Make sure existing tests pass (`pnpm test`).
+☐ Make sure the build completes successfully (`pnpm build`).
+☐ Make sure your code is [formatted properly with Prettier](#code-formatting) (`pnpm format:check`).
+☐ If adding a new feature, also add tests for it.
 ☐ If your changes affect user-facing functionality, update the relevant documentation.
 
 ### Tests
@@ -364,4 +364,4 @@ The recommended way to develop and test changes is to use the watch mode build a
 
 4. Test your changes in your test project. The changes will be automatically reflected since the package is linked via the `file:` protocol.
 
-This workflow allows for rapid iteration and testing during development.
+This workflow allows for rapid iteration and testing during development.

README.md

@@ -2,7 +2,7 @@
 
 <p align="center">
     <br/>
-    <picture> 
+    <picture>
         <source media="(prefers-color-scheme: dark)" srcset="https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/transformersjs-dark.svg" width="500" style="max-width: 100%;">
         <source media="(prefers-color-scheme: light)" srcset="https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/transformersjs-light.svg" width="500" style="max-width: 100%;">
         <img alt="transformers.js javascript library logo" src="https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/transformersjs-light.svg" width="500" style="max-width: 100%;">
@@ -31,7 +31,7 @@ Transformers.js is designed to be functionally equivalent to Hugging Face's [tra
   - 🗣️ **Audio**: automatic speech recognition, audio classification, and text-to-speech.
   - 🐙 **Multimodal**: embeddings, zero-shot audio classification, zero-shot image classification, and zero-shot object detection.
 
-Transformers.js uses [ONNX Runtime](https://onnxruntime.ai/) to run models in the browser. The best part about it, is that you can easily [convert](#convert-your-models-to-onnx) your pretrained PyTorch, TensorFlow, or JAX models to ONNX using [🤗 Optimum](https://github.com/huggingface/optimum#onnx--onnx-runtime). 
+Transformers.js uses [ONNX Runtime](https://onnxruntime.ai/) to run models in the browser. The best part about it, is that you can easily [convert](#convert-your-models-to-onnx) your pretrained PyTorch, TensorFlow, or JAX models to ONNX using [🤗 Optimum](https://github.com/huggingface/optimum#onnx--onnx-runtime).
 
 For more information, check out the full [documentation](https://huggingface.co/docs/transformers.js).
 

packages/transformers/docs/source/guides/dtypes.md

@@ -5,7 +5,7 @@ Before Transformers.js v3, we used the `quantized` option to specify whether to
 The list of available quantizations depends on the model, but some common ones are: full-precision (`"fp32"`), half-precision (`"fp16"`), 8-bit (`"q8"`, `"int8"`, `"uint8"`), and 4-bit (`"q4"`, `"bnb4"`, `"q4f16"`).
 
 <p align="center">
-    <picture> 
+    <picture>
         <source media="(prefers-color-scheme: dark)" srcset="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/blog/transformersjs-v3/dtypes-dark.jpg" style="max-width: 100%;">
         <source media="(prefers-color-scheme: light)" srcset="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/blog/transformersjs-v3/dtypes-light.jpg" style="max-width: 100%;">
         <img alt="Available dtypes for mixedbread-ai/mxbai-embed-xsmall-v1" src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/blog/transformersjs-v3/dtypes-dark.jpg" style="max-width: 100%;">

packages/transformers/docs/source/guides/webgpu.md

@@ -2,7 +2,7 @@
 
 WebGPU is a new web standard for accelerated graphics and compute. The [API](https://developer.mozilla.org/en-US/docs/Web/API/WebGPU_API) enables web developers to use the underlying system's GPU to carry out high-performance computations directly in the browser. WebGPU is the successor to [WebGL](https://developer.mozilla.org/en-US/docs/Web/API/WebGL_API) and provides significantly better performance, because it allows for more direct interaction with modern GPUs. Lastly, it supports general-purpose GPU computations, which makes it just perfect for machine learning!
 
-> [!WARNING]  
+> [!WARNING]
 > As of October 2024, global WebGPU support is around 70% (according to [caniuse.com](https://caniuse.com/webgpu)), meaning some users may not be able to use the API.
 >
 > If the following demos do not work in your browser, you may need to enable it using a feature flag:

packages/transformers/docs/source/integrations/vercel-ai-sdk.md

@@ -6,7 +6,7 @@ This guide covers the core concepts and API patterns. For a full step-by-step pr
 
 ## Why use the Vercel AI SDK with Transformers.js?
 
-The `@browser-ai/transformers-js` provider builds on top of `@huggingface/transformers` to give you a standard AI SDK interface — handling Web Worker setup, message passing, progress tracking, streaming, interrupt handling, and state management, so you can use the same `streamText`, `generateText`, and `useChat` APIs you'd use with any other AI SDK provider. 
+The `@browser-ai/transformers-js` provider builds on top of `@huggingface/transformers` to give you a standard AI SDK interface — handling Web Worker setup, message passing, progress tracking, streaming, interrupt handling, and state management, so you can use the same `streamText`, `generateText`, and `useChat` APIs you'd use with any other AI SDK provider.
 Read more about this [here](https://www.browser-ai.dev/docs/ai-sdk-v6/transformers-js/why).
 
 ## Installation